pseudomean {pseudo} | R Documentation |
Computes pseudo-observations for modeling survival function based on the restricted mean.
pseudomean(time,event, tmax)
time |
the follow up time. |
event |
the status indicator: 0=alive, 1=dead. |
tmax |
the maximum cut-off point for the restricted mean. If missing or larger than the maximum follow up time, it is replaced by the maximum follow up time. |
The function calculates the pseudo-observations for the restricted mean survival for each individual at prespecified time-points.
The pseudo-observations can be used for fitting a regression model with a generalized estimating equation.
No missing values in either time
or event
vector are allowed.
Please note that the output of the function has changed and the usage is thus no longer the same as in the reference paper - the new usage is described in the example below.
A vector of pseudo-observations for each individual.
Klein J.P., Gerster M., Andersen P.K., Tarima S., POHAR PERME, M.: "SAS and R Functions to Compute Pseudo-values for Censored Data Regression." Comput. methods programs biomed., 2008, 89 (3): 289-300
library(KMsurv)
data(bmt)
#compute the pseudo-observations:
pseudo = pseudomean(time=bmt$t2, event=bmt$d3,tmax=2000)
#arrange the data
a <- cbind(bmt,pseudo = pseudo,id=1:nrow(bmt))
#fit a regression model for the mean time
library(geepack)
summary(fit <- geese(pseudo ~ z1 + as.factor(z8) + as.factor(group),
data = a, id=id, jack = TRUE, family=gaussian,
corstr="independence", scale.fix=FALSE))
#rearrange the output
round(cbind(mean = fit$beta,SD = sqrt(diag(fit$vbeta.ajs)),
Z = fit$beta/sqrt(diag(fit$vbeta.ajs)), PVal =
2-2*pnorm(abs(fit$beta/sqrt(diag(fit$vbeta.ajs))))),4)